Target probe placement for lung ultrasound

ABSTRACT

The present disclosure describes an ultrasound imaging system configured to identify a target placement of an ultrasound probe for viewing a lung pleural line. In some examples, the system may include an ultrasound probe configured to receive ultrasound echoes from a subject to image a region of the subject and a data processor in communication with the ultrasound probe. The data processor may be configured to identify one or more candidate pleural lines and one or more A-lines corresponding to the candidate pleural lines, compute an A-line intensity of at least one of the A-lines, and apply the computed A-line intensity to indicate a target placement of the ultrasound probe for imaging the region for pleural line identification. The system may also include a user interface in communication with the data processor. The user interface may be configured to alert the user of the target placement of the ultrasound probe.

RELATED APPLICATION

This application claims the benefit of and priority to U.S. Provisional Application No. 62/433,330, filed Dec. 13, 2016, which is incorporated by reference in its entirety.

BACKGROUND

Lung ultrasound can be performed by positioning the ultrasound transducer both longitudinally, perpendicular to the ribs, and obliquely, along the intercostal spaces. At present, lung ultrasound is used to diagnose many typical conditions, for example: pneumothorax (“PTX”), pneumonia, pulmonary edema and others. The pleural line, which marks the interface between the chest wall and the lung, may be one of the first and most critical features identified during a lung ultrasound scan. Evaluation of the pleural line frequently provides a starting point for pinpointing additional lung features, including lung sliding, B-line visualization, and/or lung consolidation. As such, inaccurate imaging and/or characterization of the pleural line may interfere with downstream medical analyses. Visualizing the pleural line using conventional techniques can be difficult, especially for inexperienced ultrasound users. Techniques for a more precise, user-friendly, and in some cases automated approach to detect and/or visualize the pleural line may be desired.

SUMMARY

Provided herein are ultrasound systems and methods for improved pleural line identification and imaging. Various examples identify and process visual artifacts generated by reverberating ultrasound echoes. These artifacts, sometimes referred to as “A-lines,” may appear when imaging particularly echogenic features, such as the pleural interface. In some examples, A-lines may be especially bright when ultrasound echoes reflecting off the pleural interface are most intense, which may occur when the ultrasound probe performing the imaging is positioned and/or oriented in a particular placement that enhances the intensity of the ultrasound signals. The systems disclosed herein may include an ultrasound probe configured to receive ultrasound echoes, and a data processor configured to process candidate pleural lines and A-lines, compute the intensity of at least one A-line, and apply this intensity to determine the target placement of the probe for pleural line identification.

In accordance with some examples, an ultrasound imaging system may include an ultrasound probe configured to receive ultrasound echoes from a subject to image a region of the subject. The ultrasound imaging system may further include a data processor in communication with the ultrasound probe. The data processor may be configured to identify one or more candidate pleural lines and one or more A-lines corresponding to the candidate pleural lines, compute an A-line intensity of at least one of the A-lines, and apply the computed A-line intensity to indicate a target placement of the ultrasound probe for imaging the region for pleural line identification. In some examples, the ultrasound system may further include a user interface in communication with the data processor. The user interface may be configured to alert the user of the target placement of the ultrasound probe.

In some embodiments, the computed A-line intensity may exceed a predetermined threshold when the target placement is satisfied. In some examples, the target placement may involve a position or an orientation of the ultrasound probe.

In some implementations, the data processor may be further configured to reject one or more candidate pleural lines by determining whether one or more candidate pleural lines satisfy a predetermined pleural line intensity threshold. In some embodiments, the data processor may be further configured to identify one or more sub-regions of an ultrasound data frame that correspond to an estimated depth of one or more candidate pleural lines. In some examples, the data processor may be further configured to identify one or more sub-regions of an ultrasound data frame that correspond to an estimated depth of one or more A-lines. In some implementations, the data processor may be further configured to identify a first A-line intensity measured at a first time, and a second A-line intensity measured at a second time, the first time different from the second time. In some embodiments, the data processor may be further configured to identify an A-line intensity variation, the A-line intensity variation equal to an intensity difference between the first A-line intensity and the second A-line intensity.

In some examples, the user interface may be configured to alert the user by providing an indicator to the user, where the indicator may be configured to provide an absolute signal, such that the signal is either in an “On” state when the probe is in the target placement or an “Off” state when the probe is not in the target placement. In some implementations, the user interface may be configured to alert the user by providing an indicator to the user, where the indicator is configured to provide a relative signal that changes in response to variations in A-line intensity that result from repositioning or reorienting the ultrasound probe. In some embodiments, the one or more A-lines may appear at depths that are about multiple integers of a depth of the one or more candidate pleural lines.

A method in accordance with the present disclosure may involve acquiring image data of a region of a lung tissue via an ultrasound probe, detecting, using the data, one or more candidate pleural lines and one or more A-lines corresponding to the candidate pleural lines, computing an A-line intensity of at least one of the A-lines, and applying the computed A-line intensity to indicate a target placement of the ultrasound probe for pleural line identification during image data acquisition of the region. In some examples, the method may further include alerting a user of the target placement of the ultrasound probe via a user interface. In some embodiments, the computed A-line intensity may exceed a predetermined threshold when the target placement is satisfied. In some implementations, the target placement may involve a position or an orientation of the ultrasound probe.

In some embodiments, detecting, using the data, one or more candidate pleural lines may involve determining whether one or more unidentified lines are located within a predetermined depth range or whether one or more unidentified lines satisfy a predetermined pleural line intensity threshold. In some embodiments, detecting, using the data, one or more A-lines may involve applying a Hough transform to the data. In some implementations, detecting, using the data, one or more A-lines may involve determining a depth corresponding to a peak intensity level detected at one or more lateral positions in the region of the lung tissue.

Additionally, any of the techniques for identifying a target placement of an ultrasound probe for viewing a pleural line may be embodied in executable instructions stored on non-transitory computer-readable medium, which when executed cause a processor of a medical imaging system to be programmed to perform the processes embodied in the non-transitory computer-readable medium.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of an ultrasound imaging system in accordance with the principles of the present disclosure.

FIG. 2 is a block diagram of an ultrasound imaging apparatus in accordance with the principles of the present disclosure.

FIG. 3 is a block diagram of an ultrasound imaging method in accordance with the principles of the present disclosure.

FIG. 4 is a block diagram of an ultrasound imaging system in accordance with the principles of the present disclosure.

FIG. 5 is a lung ultrasound image taken with a sub-optimal orientation of the probe in accordance with the principles of the present disclosure.

FIG. 6 is a lung ultrasound image taken with a target placement of the probe in accordance with the principles of the present disclosure.

DETAILED DESCRIPTION

The following description of certain exemplary embodiments is merely exemplary in nature and is in no way intended to limit the invention or its applications or uses. In the following detailed description of embodiments of the present systems and methods, reference is made to the accompanying drawings which form a part hereof, and in which are shown by way of illustration specific embodiments in which the described systems and methods may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the presently disclosed systems and methods, and it is to be understood that other embodiments may be utilized and that structural and logical changes may be made without departing from the spirit and scope of the present system. Moreover, for the purpose of clarity, detailed descriptions of certain features will not be discussed when they would be apparent to those with skill in the art so as not to obscure the description of the present system. The following detailed description is therefore not to be taken in a limiting sense, and the scope of the present system is defined only by the appended claims.

The present technology is also described below with reference to block diagrams and/or flowchart illustrations of methods, apparatus (systems) and/or computer program products according to the present embodiments. It is understood that blocks of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations, may be implemented by computer executable instructions. These computer executable instructions may be provided to a processor, controller or controlling unit of a general purpose computer, special purpose computer, and/or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer and/or other programmable data processing apparatus, create means for implementing the functions/acts specified in the block diagrams and/or flowchart block or blocks.

Lung ultrasound techniques often involve assessing the pleural interface by visualizing at least a portion of a pleural line, which may serve as a reference point for identifying additional lung features. Standardization and automation tasks, in particular, may depend on precise pleural line visualization. In a normal lung, the pleural interface is an echogenic specular reflector due to the substantial contrast between the tissue of the chest wall and an air-filled lung. However, the brightness level of the displayed pleural line may be particularly sensitive to the position and/or orientation of the ultrasound probe held by a technician. Positioning the ultrasound probe perpendicular to the pleural interface may produce a clear image of a pleural line while other positions and/or angular orientations of the probe may cause at least a portion of the ultrasonic echoes to reflect off the pleural interface in a direction away from the probe, thus reducing the intensity of the pleural line in the image. In addition, anatomical variations may prevent ultrasound users, especially those lacking experience, from orienting the ultrasound probe in a manner necessary to obtain a clear pleural line image, thus impeding the overall quality of the lung ultrasound examination. For example, even if an ultrasound user attempts to position the ultrasound probe perpendicular to the pleural interface, shifting of the pleura or variations in the volume of a lung during respiration within the patient may complicate the process and obscure the ultrasound feedback.

In some circumstances, additional horizontal lines may appear on an ultrasound image at positions that appear deeper than the pleural line. These horizontal lines, often termed “A-lines,” do not represent structural, anatomical features of the lungs. Instead, they represent artifacts formed by ultrasound echoes reverberating between the pleural interface and the ultrasound probe. Because each reverberation of the ultrasound echo takes the same or substantially similar amount of time to be detected by the probe as the initial time interval between signal emission, reflection off the pleura, and detection at the probe, each A-line may appear at a depth at or about equal to a multiple of the actual depth of the pleural line. For instance, the first A-line may appear at or about double the depth of the pleural line, the second A-line may appear at or about triple the depth of the pleural line, and so on. The systems and methods described herein may enhance pleural line visualization by detecting A-lines that may appear during ultrasound imaging. In some examples, the systems and methods described herein may determine an ultrasound probe position and/or orientation that optimizes or enhances a pleural line image by detecting A-lines of high intensity. In some examples, feedback of a target probe placement which may be based on the detected pleural and/or A-lines may be provided to a user.

FIG. 1 shows an example ultrasound system 100 configured to identify a target placement of an ultrasound probe relative to the pleural interface to enhance the quality of an image of a pleural line in accordance with the present disclosure. As shown, the system 100 may include an ultrasound data acquisition unit 110, which includes, in some embodiments, an ultrasound probe 112 configured to receive ultrasonic echoes 114 from a medium, a beamformer 116 and a signal processor 118. The system also includes a data processor 120, e.g., a computational module or circuitry, configured to detect a pleural line based on the ultrasonic echoes 114 received by the probe 112. The data processor 120 may be further configured to identify one or more A-lines produced by reverberating pleural line echoes. In some examples, the data processor 120 may be configured to compute intensity values of at least one of the A-lines and using this information, identify when a target placement of the probe 112, relative to the pleural interface, is obtained. The system 100 may also include a user interface 122 configured to provide images 124 (e.g., B-mode images) such as on a display operatively associated with the system 100 and/or a probe orientation indicator 126. The probe orientation indicator 126 may indicate when the probe 112 is oriented in a target position and/or orientation for viewing the pleural line and may be generated responsive to signals from the data processor 120. In some embodiments, the probe orientation indicator 126 may be provided visually such as on the display on or adjacent to the images 124. In other embodiments, the probe orientation indicator 126 may be provided visually elsewhere such as via illumination of a light source, audibly such as via the sounding of a tone, or tactily such as via a slight vibration of the probe. In embodiments, the system 100 can be a stand-alone ultrasound diagnostic imaging system either fixedly mounted or equipped with wheels to enable movement. The system 100 can be a compatible, portable device such as a laptop, a tablet, a smart phone or the like in some examples. The ultrasound probe can be connectable, for example via a USB interface, to any suitable portable device.

The ultrasound data acquisition unit 110 may be configured to acquire ultrasound data for one or more regions of interest selectable by a user. According to embodiments of the present disclosure, the selected regions encompass at least a portion of a lung that includes the pleural interface. To generate ultrasound data in the region(s) of interest, the data acquisition unit 110 includes an ultrasound probe 112. The ultrasound probe 112 is the component held and manipulated by a user, e.g., a sonographer, clinician or ultrasound technician, during ultrasound examination. The ultrasound probe 112 may be configured to transmit ultrasonic energy into the region of interest, e.g., the chest region of a patient subject, and receive corresponding ultrasound echoes such that at least a portion of the lungs may be imaged. To transmit and receive ultrasound echoes, the probe 112 includes at least one transducer array. A variety of transducer arrays are well known in the art, e.g., linear arrays, convex arrays or phased arrays. The transducer array included in the probe 112, for instance, can include a two dimensional array of transducer elements capable of scanning in both elevation and azimuth dimensions for 2D and/or 3D imaging.

As further shown in FIG. 1, the probe 112 may be coupled to a beamformer 114, e.g., a microbeamformer. The beamformer 114 may be coupled within the probe 112, controlling the transmission and reception of ultrasound signals by the transducer elements positioned therein. In particular, the beamformer 114 may be configured to beamform the ultrasound signals to produce coherent echoes, such as ultrasound raw radiofrequency data.

In some embodiments, the beamformed signals can be communicated or coupled to the signal processor 116. The signal processor 116 may be configured to process the received echo signals in various ways, such as bandpass filtering, decimation, I and Q component separation, and harmonic signal separation. The signal processor 116 can derive various ultrasound data, such as ultrasound B-mode data, radio frequency (RF) data, and/or Doppler data from the received ultrasound echo signals. In some examples, the signal processor 116 may detect amplitudes of the received ultrasound signals for imaging structures in the body, such as the lungs, lung components, e.g., the pleural interface, and/or anatomical structures surrounding the lungs. The signal processor 116 can further arrange the echo signals in the spatial relationship from which they were received to form at least one ultrasound data frame. Multiple ultrasound data frames received by the signal processor may be arranged according to their order of receipt, forming a temporal sequence of frames.

The ultrasound acquisition unit 110 may be configured to acquire, via the ultrasound probe 112, beamformer 114 and/or signal processor 116, ultrasound data corresponding to at least one region of interest that includes the pleural interface or a portion thereof. Techniques employed by a user to acquire such data, via the acquisition unit 110, may vary. In some examples, the probe 112 may be positioned longitudinally, in an orientation perpendicular to the ribs, or obliquely, along the intercostal spaces between the ribs. In some embodiments, the probe may be fanned, waved, or otherwise repositioned with respect to the patient. Modifying the position of the probe 112 may alter the angular orientation of the probe 112 relative to the pleural interface. As a result, the quality and/or number of ultrasound echoes received by the probe 112 may vary for different features, such as the pleural line, as evidenced by variation in the brightness intensity levels and/or resolution of such features displayed on a user interface.

Examples of data acquired by the ultrasound acquisition unit 110 may include 2D or 3D datasets. The dataset(s) may include a plurality of data frames acquired in real time or substantially real time, each frame corresponding to a region of interest that includes at least a portion of the pleural interface. The ultrasound data acquired by the data acquisition unit 110 may include echo intensity information for any given point (or coordinate location) within the imaged volume. For example, a 3D dataset may include voxel data that specifies the x, y, z coordinates for each voxel in the data along with the echo intensity value at each voxel.

The components of the data acquisition unit 110, and their specific arrangement with respect to one another, may vary in different embodiments. For example, the beamformer 114 and the signal processor 116 are illustrated as two separate units, but a person skilled in the art would appreciate that they are logic or functional units, and they can be implemented in a single unit or each of them can be implemented by more than one separate unit. Further, the ultrasound probe 112 may be configured to perform additional functions pursuant to ultrasound data acquisition, including one or more functions of the beamformer 114 and/or signal processor 116. More or less components may be considered as part of the data acquisition unit 110. (see, for e.g., FIG. 4)

As further show in FIG. 1, the system 100 may include a data processor 120 operatively, physically, and/or communicatively coupled to one or all components of the data acquisition unit 110. In operation, the data processor 120 may be configured to receive and process ultrasound data, e.g., a plurality of ultrasound data frames, acquired by the ultrasound acquisition unit 110. According to embodiments of the present disclosure, the data processor 120 may be particularly configured to process the received ultrasound data to identify one or more candidate pleural lines and one or more A-lines corresponding to the candidate pleural lines. Using this information, the data processor 120 may be further configured to identify the position and/or orientation of the probe 112 that produces the best, or at least a clear, image of the pleural line, hereinafter referred to as the “target placement” of the probe. The target placement may include the probe position and/or orientation that maximizes the brightness intensity and/or resolution of the pleural line, or otherwise enhances the clarity of the line for visual examination. As disclosed herein, the target placement of the probe may be identified by assessing the intensity levels of one or more A-lines. In embodiments, automatic detection of one or more candidate pleural lines and one or more A-lines can be implemented by any suitable existing and future-developed detection algorithm. In some embodiments, the receipt and/or processing of data by the data processor 120 may be performed in real time or substantially real time, as the data is acquired, thus enabling a user to be continuously updated regarding the quality of the probe position and/or orientation with respect to the pleural line.

In some embodiments, the data processor 120 may be configured to identify, within each ultrasound data frame received from the acquisition unit 110, one or more sub-regions that include at least a portion of the pleural line and one or more A-lines. Data extracted from these sub-regions may be subjected to additional processing to pinpoint, from a number of candidates, the pleural line and any corresponding A-lines. These features may be further analyzed by the data processor 120 to determine which probe position and/or orientation produces the best pleural line image.

In some examples, one or more sub-regions may be identified by the data processor 120 based on one or more predetermined parameters. The parameters may include a predetermined depth range. In some embodiments, the predetermined depth range may encompass the estimated depth of the pleural line, which may range from about 1.5 cm to about 5 cm from the top surface, e.g., the skin surface, of the scanned region. To ensure that the pleural line is included in the sub-region, the predetermined depth range applied to the ultrasound data may be broader, ranging from about 0.5 to about 7 cm, for example. In some embodiments, the predetermined depth range may vary depending on the characteristics of the patient being scanned. For instance, the pleural interface depth may be greater for patients having a higher body mass index. Due to this variation, one or more landmarks of consistent depth, e.g., ribs, may be used as a reference point by the data processor 120.

Additional or alternative sub-regions may correspond to predetermined, estimated depth(s) of one or more A-lines produced by pleural line reverberation signals. The A-line sub-region depths may be estimated based on the understanding that A-lines are produced by ultrasound echoes that reflect off the pleural interface and return to the probe 112, only to be reflected back into the scanned region a second time, reflecting off the pleural interface at least once more. Because the secondary reflections may take approximately twice as long to be received by the probe 112 compared to the primary reflections, the secondary reflections may appear to be derived from twice the depth of the pleural interface. Thus, the A-line sub-region depths may be defined to encompass twice the depth of the estimated pleural line depth. In some examples, this may correspond to a depth range of about 1 to about 14 cm, about 1 to about 12 cm, or about 2 to about 11 cm.

In some examples, the ultrasonic echoes may reverberate between the pleural interface and the probe 112 more than two times. For instance, the ultrasound echoes may reverberate back and forth between the probe 112 and pleural line two, three, four or more times, thus producing two, three, four or more A-lines. As a result, additional sub-regions may be specified by the data processor 120 to capture additional A-line data within the ultrasound frame(s). Because the plurality of A-lines may be equally spaced, each A-line sub-region may encompass multiple integers of the pleural line depth. Thus, for a second A-line, the depth may correspond to three times the estimated pleural line depth. This may correspond to a range of about 1 to about 21 cm, about 1.5 to about 18 cm, or about 2 to about 16.5 cm in some examples.

In some embodiments, each sub-region may correspond to the anticipated depth of one pleural line or one A-line. In other examples, sub-regions may be defined by the data processor 120 to include more than one A-line and/or the pleural line. Implementations may also include an A-line sub-region, defined to include one or all A-lines, and a pleural line sub-region, thus distinguishing sub-regions based one whether the feature shown in each sub-region is real or merely an artifact. Embodiments may also include a single, all-encompassing sub-region defined to cover a range that includes both the pleural line and all A-lines.

In still other embodiments, the data processor 120 may not be configured to identify any sub-regions within each ultrasound data frame. Such embodiments may process each ultrasound data frame as a whole, searching for the pleural line and one or more A-lines without specifying a sub-region. In some embodiments, the system 100 may be configured to selectively incorporate sub-region parameters automatically or in response to a user input 128.

Additional or alternative techniques may be employed by the data processor 120 to estimate the depth of the pleural line and/or one or more A-lines. In some examples, the depth may be estimated by the data processor 120 using one or more ultrasound data frames collected in sequence. In particular, embodiments may involve creating an intensity profile that represents intensity values as a function of depth at a number of lateral positions encompassed by an ultrasound scan. The lateral positions may be predetermined and may include the center lateral position along the scan line. In addition or alternatively, the lateral positions may include multiple positions equidistant from the center lateral position. The intensity value at a certain depth can be a sum, average, and/or weighted average value of all ultrasound data values at that depth measured in multiple ultrasound data frames. For instance, the depth that produces, on average, the highest measured intensity peak value may serve as the initial search depth for locating a pleural line and/or an A-line. The central lateral position may be used, in some examples, as the initial lateral location for conducting the pleural/A-line search.

In various embodiments, the depth of the pleural line and/or A-lines may be estimated using one or more additional features. For example, the pleural line depth may be estimated by first estimating the depth of at least one rib, and adding a predetermined distance to the estimated rib depth, the predetermined distance comprising the average separation between the rib and the pleural interface. The number, spatial location and/or orientation of ultrasound data frames used to calculate the predicted depth may vary. Upon identifying an estimated depth of the pleural line and/or one or more A-lines, the data processor 120 may be configured to detect the pleural line and/or A-lines according to any suitable detection algorithm. The algorithm may gradually expand the search area for the pleural and/or A-lines using the initial estimation as a starting point. In particular, after a candidate peak is located on a central line by identifying highest peak amplitude, the algorithm may move outward from central line in both directions looking for correlations to piece together a horizontal line feature that represents a pleural line or an A-line.

Whether or not pleural and/or A-line sub-regions are established or depths of either feature estimated, the data processor 120 may be configured to identify a pleural line within one or more data frames received from the ultrasound data acquisition unit 110. The techniques implemented by the data processor 120 to identify the pleural line may vary in different embodiments. For instance, the data processor 120 may be configured to identify the pleural line based at least in part on the identification of one or more A-lines. Such an approach reflects the understanding that A-lines may be more likely to appear upon reflecting ultrasound energy directly off the pleural interface. In other embodiments, pleural line candidates may be identified based on intensity levels of various features detected by the acquisition unit 110. In some embodiments, pleural line identification may be carried out by the data processor 120 in an automated or semi-automated manner using one or more algorithms.

As mentioned, in some embodiments the data processor 120 may be configured to identify a pleural line by identifying line features that produce reverberation artifacts, or A-lines. According to this approach, pleural line candidates include line features that produce A-lines. Thus, unidentified lines detected by the acquisition unit 110 that may appear in the correct vicinity and/or at a characteristic pleural line intensity level may be excluded from the list of pleural line candidates if such lines are not accompanied by corresponding A-lines. The data processor 120 may be configured to search one or multiple A-line sub-regions to identify potential A-lines. In addition, A-line candidates may be rejected if, for instance, the A-line candidates do not appear equidistant from each other and/or at multiple integer depths of the candidate pleural line. In some embodiments, the data processor 120 may be configured to, upon identifying a plurality of equally spaced lines, choose the most shallow line as the likely pleural line, designating the deeper lines as A-lines.

In some embodiments, the data processor 120 may be configured to identify candidate pleural lines by determining and/or processing the intensity levels, e.g., brightness, of the return signals produced by various features detected by the data acquisition unit 110. Because the pleural line may produce strong echo signals, and thus increased intensity levels relative to other features in the region of interest, the data processor 120 may be configured to eliminate line features producing intensity levels below a specified, e.g., predetermined, pleural line intensity threshold. Thresholding techniques may vary. In some examples, a predetermined intensity threshold may be calculated based on empirically-derived ultrasound data. Such statistical data may include an average of measured pleural line intensity levels acquired over a period of time. In some examples, the averaged intensity levels may be tiered according to certain patient characteristics. For instance, average intensity levels may be grouped based on body mass index and/or rib depth/position. In embodiments, the predetermined intensity threshold applied to the received ultrasound data may be set below the calculated average intensity level. This may ensure that pleural lines producing unusually low intensity levels are not excluded from further analysis. In some embodiments, the predetermined intensity threshold may be patient-specific. According to such examples, previously measured intensity levels for a particular patient may be stored in memory and used by the data processor 120 to quickly identify the pleural line when performing subsequent ultrasound scans.

In some examples, the data processor 120 may be configured to identify candidate pleural and/or A-lines by identifying intensity levels at one or more boundary lines in a scanned ultrasound image. In particular, the processor 120 may be configured to determine a point at which the intensity values of a plurality of scanning lines increases above a certain intensity threshold. The processor 120 may designate this point as the starting point of the pleural line or A-line. The processor may also designate the end point of the line as the location at which the brightness value of the line drops below a predetermined threshold. In some embodiments, the starting point and end point may be determined based on a change in intensity levels, such that an intensity threshold is established based on an increase in intensity levels (e.g., at the starting point) and a decrease in intensity levels (e.g., at the ending point). The change may be absolute in some examples, and based on a calculated slope in other examples.

In some embodiments, the data processor 120 may be configured to first identify one or more candidate pleural lines based on intensity thresholding, for example, followed by a search for one or more A-lines that correspond to such candidates. In some examples, the data processor 120 may be configured to apply a similar intensity threshold with respect to A-lines, excluding from the list of A-line candidates those lines that fail to produce return echoes satisfying or exceeding a predetermined intensity threshold. Pleural line candidates previously identified based on intensity level may be rejected if no corresponding A-lines are identified by the data processor 120. To ensure real time or substantially real time processing, the data processor 120 may be configured to identify candidate pleural lines and corresponding candidate A-lines in quick, nearly simultaneous succession. As disclosed herein, the data processor 120 may also be configured to identify pleural line candidates and A-lines concurrently, or to identify pleural lines or pleural line candidates by first identifying one or more A-lines.

In some embodiments, the data processor 120 may implement a Hough transform to identify a pleural line and/or one or more A-lines. Hough transform processes may be incorporated into any of the above techniques for identifying a pleural line and/or A-lines.

In some examples, an ultrasound data map derived by the data processor 120, or a component communicatively coupled thereto, may be incorporated into the pleural/A-line identification process. The data map may be filtered or unfiltered and may be derived from any two or more frames of ultrasound data acquired by the data acquisition unit 110. In some examples, one or more correlation maps may also be derived by the processor 120 by utilizing more than two frames of ultrasound data. Correlation maps may be derived using amplitude data extracted from ultrasound radio frequency data in some examples.

After identifying the pleural line and one or more corresponding A-lines, the data processor 120 may be configured to determine the target placement of the probe for imaging the pleural line. In embodiments, the target placement of the probe may correspond to the position and/or orientation of the probe 112 that maximizes or enhances the intensity values of the one or more identified A-lines. According to such embodiments, the data processor 120 may continuously receive and process the intensity values of previously identified A-lines. As the user changes the position and/or orientation of the probe 112 with respect to the pleural interface, the number and/or intensity of the corresponding A-lines may vary. The data processor 120 may be configured to monitor the variations in A-line intensity as the probe 112 is moved and determine the precise moment, or ultrasound data frame, at which the A-line intensity is maximized or increased. In operation, the data processor 120 may be configured to identify the target placement of the probe by implementing one or more algorithms that detect the presence of one or more A-lines and the intensity level(s) thereof. In addition or alternatively, the data processor 120 may be configured to determine the average intensity of a region surrounding the pleural line, identifying increases or decreases in the intensity of such a region as the probe position and/or orientation is adjusted, regardless of whether A-lines are detected.

In embodiments, the number of A-lines may increase with increased echogenicity of the pleural line. For example, the number and/or intensity of A-lines may increase when the probe 112 is aimed directly, e.g., perpendicularly, at the pleural interface. Accordingly, the data processor 120 may also be configured to monitor the number of A-lines produced from echo signals reflecting from the identified pleural line. When the number of A-lines is maximized or increased, the data processor may prompt the user interface 122 to alert the user that the target placement of the probe has been attained.

In some examples, the data processor 120 may be configured to identify the target placement of the probe by implementing an intensity thresholding process. In particular, the data processor may be configured to continuously compare the intensity values of one or more of the identified A-lines against a predetermined intensity threshold. Intensity levels exceeding the predetermined threshold may indicate that the target placement of the probe has been attained. The threshold value may be determined based on experimentally-obtained data regarding the correlation between A-line intensity and the intensity and/or resolution of the pleural line. Specifically, the A-line intensity threshold value may be determined based on whether such an intensity value, on average, is associated with pleural line images sufficiently clear for examination.

At the moment the data processor 120 determines that A-line intensity is maximized and/or exceeds a specified intensity threshold, the data processor 120 may be configured to communicate this information to the user interface 122, which then communicates a probe orientation indicator 126 alerting to a user that the target placement of the probe has been attained.

The user interface 122, which may be operatively, physically, and/or communicatively coupled to the data processor 120, may be configured to communicate the probe orientation indicator 126 to the user in real time or substantially real time. The indicator 126 may be conveyed in various ways. For example, the indicator 126 may include various graphics, icons, or visual aids displayed on the user interface 122. Such signals may be overlaid on an ultrasound B-mode image displayed on the user interface 122 or away from the image. In some examples, the indicator 126 may be represented by a change in formatting, e.g., flashing, or a change in color of a feature displayed on the user interface 122. In additional embodiments, the indicator 126 may include an audio cue, e.g., beeping, that sounds at the moment the target placement of the probe is attained.

In various embodiments, the characteristics of the probe orientation indicator 126 may depend, at least in part, on the amount and/or nature of data communicated from the data processor 120 to the user interface 122. For instance, the indicator 126 may include an absolute, all-or-nothing signal that only appears at the moment the target placement of the probe is obtained. Such an absolute indicator 126 may disappear the moment the probe 112 is re-positioned away from the optimal probe position, such that the signal is either in an “On” state when the probe is in the target placement or an “Off” state when the probe is not in the target placement. According to such embodiments, the data processor 120 may send an indication that the target placement of the probe has been obtained when the A-line intensity values are maximized and/or when the A-line intensity values exceed a predetermined threshold.

In other examples, the probe orientation indicator 126 may be a gradual, relative signal indicating whether the orientation of the probe 112 is improving or worsening with respect to the target placement of the probe. According to such embodiments, the data processor 120 may be configured to compare a current ultrasound data frame to the data obtained from the preceding frame, automatically communicating the results of such a comparison to the user interface 122 for display in the form of the indicator 126. In particular, the data processor 120 may compare ultrasound data frames received from the data acquisition unit 110 in a constant, continuous fashion, such that every data frame received from the acquisition unit 110 is automatically compared to at least one previously-obtained data frame. The data processor 120 may compare A-line intensity values for each data frame received, assessing whether intensity levels obtained from the current position of the probe 112 are more or less intense than the intensity levels obtained from the preceding probe position. In some embodiments, an increase in A-line intensity levels may be indicated by a change in the indicator 126 displayed on the user interface 122. Likewise, a decrease in intensity levels may also be indicated by the indicator 126. In some examples, the change in A-line intensity levels may be communicated by changing a color of the indicator 126, for e.g., the signal may appear green when the intensity levels are higher in the current probe position and/or orientation than the preceding probe position and/or orientation, and red when the intensity levels produced by the current probe position/orientation are lower than as measured from the previous frame. The color may change to blue, for instance, upon positioning or orienting the probe in the target placement. In additional embodiments, the indicator 126 may include a change in the color and/or display of the pleural line and/or corresponding A-lines. For instance, the user interface 122 may label the identified pleural line with a graphic, such as a line that traces the pleural line. At the moment the user interface 122 receives an indication from the data processor 120 that the target placement has been obtained, the user interface 122 may convey the indicator 126 in the form of a change in color and/or format of the graphic.

In some embodiments, the user interface 122 may be configured to receive indications of user input 128 and/or display various outputs. For example, the user interface 122 may be configured to display ultrasound images, e.g., B-mode images, of the pleural line and one or more A-lines. In embodiments, the detected pleural line may be overlaid on an image of the scanned region or a sub-region thereof. In some examples, the user interface 122 may be configured to receive an input 128 instructing the system 100 to initiate one or more processes described herein. The user interface 122 may also be configured to receive an input 128 changing one or more system settings and/or parameters. Such changes may be implemented upon receipt of the input 128 at the user interface 122, e.g., in real time, or prior to initiation of the methods described herein. In specific embodiments, the user interface 122 may display, for example, one or more adjustable sliding bars for adjusting one or more settings and/or parameters. At least one of the sliding bars may be used to modify the intensity threshold used to identify a pleural line, one or more candidate pleural lines, and/or one or more A-lines. In some examples, the user interface 122 may be configured to display information indicative of the identity or characteristics of the data acquired by the data acquisition unit 110 and processed by the data processor 120. For instance, the user interface 122 may label various features identified by the data processor 120, e.g., pleural line, A-lines, ribs, etc.

Once user receives the probe orientation indicator 126 that the target placement of the probe has been attained, the user may hold the probe 112 in this position and/or orientation for further examination. Identification of the target placement according to the embodiments described herein may enable the user to properly analyze additional lung features and/or thoroughly examine the features of the pleural line itself to identify, for example, lung sliding. In some examples, the user may hold the probe in the target placement while allowing the system 100 to perform further analyses, e.g., feature detection assistance protocols, in an automated or semi-automated manner. Examples of typical clinical applications may include pneumothorax and pneumonia, but the disclosures herein may be applied to a wide range of examination techniques and/or health conditions.

In some examples, the data processor 120 may be further coupled to a storage device. The storage device may be included in a separate apparatus, e.g., a hospital information system, and may be configured to retrieve the ultrasound data from the data acquisition unit 110 and/or the data processor 120. In some embodiments, the data processor 120 may include the storage device in the form of a memory, for example. In embodiments that include storage devices, the target placement of the probe may be stored in memory and extracted for application during subsequent ultrasound scans, thus facilitating repeated ultrasound monitoring over time. In particular embodiments, the target placement of the probe may be stored as a reference point, or zero point, specific to a patient being imaged. Target placements for imaging additional lung features, relative to the reference point, may be stored as well. The ultrasound imaging system 100 may instruct a subsequent user on how to properly position and/or orient the probe 112 at discrete locations on the patient's chest using the stored orientations obtained at earlier time points. Pursuant to such embodiments, the probe 112 may include one or more sensors, e.g., a gyroscope.

FIG. 2 is a block diagram of an ultrasound imaging apparatus in accordance with the principles of the present disclosure. As shown, the apparatus includes a sub-region identifier 210, along with a first sub-region identifier 210 a and a second sub-region identifier 210 b, a user interface 220, a pleural line detector 230, and an A-line detector 240. A person skilled in the art would appreciate that the components of FIG. 2 are not intended to restrict the invention, but merely to show a particular embodiment of the present invention, and some of the components may be optionally omitted or modified in various embodiments.

The apparatus 200 is configured for identifying the target placement of the probe by identifying and processing the pleural line and one or more corresponding A-lines. In some examples, the apparatus 200 can be a component of an ultrasound system, such as the data processor 120 of system 100. The apparatus 200 may also be connectable to one or more storage devices for temporarily or permanently storing ultrasound data, e.g., coordinates of the target placement of the probe. The storage devices may include the storage device of an ultrasound system, an ultrasound probe, a PACS system or other hospital information system.

The apparatus 200 may be configured to receive ultrasound data frames corresponding to a first region of interest, where the first region of interest includes at least a portion of the pleural interface. In some examples, the apparatus 200 may detect a pleural line and one or more A-lines as the ultrasound data frames are received. Accordingly, the ultrasound data frames can be sequentially received frame-by-frame in a real-time data stream by the apparatus 200.

The apparatus 200 may include one or more sub-region identifiers 210. In some examples, the sub-region identifier 210 may be configured to identify, for each ultrasound data frame, a sub-region of the frame that includes at least a portion of a pleural line and/or A-line. In some examples, the apparatus 200 may include two distinct sub-region identifiers: a first sub-region identifier 210 a configured to identify a sub-region of each data frame that includes at least a portion of a pleural line, and a second sub-region identifier 210 b configured to identify a sub-region of each data frame that includes at least a portion of one or more A-lines corresponding to a pleural line. Some examples may include additional sub-region identifiers, e.g., 210 c, 210 d, 210 e, etc., each configured to identify an additional sub-region of each data frame that includes at least a portion of an A-line. Each sub-region may be located in an area approximately one or more multiple integers of depth beneath the sub-region that includes at least a portion of the pleural line. In additional embodiments, a single sub-region identifier, such as sub-region identifier 210, may be configured to identify multiple sub-regions of each ultrasound data frame, each sub-region including at least a portion of the pleural line or an A-line.

As further shown in FIG. 2, the apparatus 200 may include a pleural line detector 230 communicatively coupled with the sub-region identifier 210. The pleural line detector 230 may be configured to identify at least a portion of a pleural line within the sub-region identified by the sub-region identifier 210. In some examples, the pleural line detector 230 may first identify a list of candidate pleural lines before ultimately rejecting candidates that fail to satisfy one or more predetermined criteria, e.g., an intensity threshold or associated A-lines. The pleural line detector 230 may implement any suitable existing and future-developed detection algorithm for identifying a pleural line within a sub-region of an ultrasound data frame.

In some examples, the pleural line detector 230 may be communicatively coupled with the A-line detector 240, which may also be coupled with the sub-region identifier 210. The A-line detector 240 may operate concurrently with the pleural line detector 230. In some embodiments, the pleural line detector 230 may operate in whole or in part based on data generated by the A-line detector 240. According to such embodiments, the pleural line detector 230 may receive, from the A-line detector 240, data regarding whether one or more candidate pleural lines, previously identified by the pleural line detector 230, are associated with corresponding A-lines in an ultrasound data frame. In other examples, the pleural line detector 230 may be configured to identify one or more candidate pleural lines after receiving, from the A-line detector 240, data regarding the identification of one or more A-lines. In some examples, the pleural line detector 230 may be configured to transmit data regarding an identified pleural line to the A-line detector 240. In various embodiments, the pleural line detector 230 and/or A-line detector 240 may be configured to determine and/or process intensity levels for one or more candidate pleural lines and A-lines, respectively. The pleural line detector 230 and the A-line detector 240 may implement any suitable existing and future-developed detection algorithm for identifying one or more pleural lines and A-lines, respectively, within a sub-region of an ultrasound data frame.

In embodiments, the A-line detector 240 may be configured to identify whether the target placement of the probe has been attained by assessing intensity levels of one or more A-lines. The A-line detector 240 may implement any suitable existing and future-developed detection algorithm for identifying the target placement. Implementations may involve applying an intensity threshold to one or more A-lines and/or comparing A-line intensity values received in successive ultrasound data frames to measure variation in A-line intensity.

The pleural line detector 230 and/or A-line detector 240 may be configured to transmit data regarding a pleural line and A-lines, respectively, to the user interface 220. This data may include an indication that the target placement has been attained. As described above, the user interface 220 may be configured to display a signal conveying this indication to a user. In embodiments, the user interface 220 may be configured to receive one or more user inputs that may alter the operation of the sub-region identifier 210, the pleural line detector 230, and/or the A-line detector 240.

FIG. 3 is a block diagram of an ultrasound imaging method in accordance with the principles of the present disclosure. The example method 300 of FIG. 3 shows the steps that may be utilized, in any sequence, by the systems and/or apparatuses described herein for optimizing or improving the position and/or angular orientation of an ultrasound probe relative to the pleural interface. For instance, the method 300 may be performed by an ultrasound imaging system, such as system 100, or other systems including, for example, a mobile system such as VISIQ by Koninklijke Philips N.V. (“Philips”). Additional example systems may include SPARQ and/or EPIQ, also produced by Philips.

In the embodiment shown, the method 300 begins at block 310 by “acquiring image data of a region of a lung tissue via an ultrasound probe.” In some examples, the image data may be acquired under the control of a user. Various types and sizes of ultrasound probes may be used. In embodiments, the probe may be a linear, curved-linear, sector, or matrix probe. In some examples, the image data may include a 2D dataset or a 3D dataset. The data may be organized in a plurality of data frames, the duration of which may vary.

At block 312, the method 300 involves “detecting, using the data, one or more candidate pleural lines and one or more A-lines corresponding to the candidate pleural lines.” Techniques used to identify candidate pleural lines may involve intensity thresholding, a Hough transform, assessment of peak intensity values versus depth, and/or the application of one or more predetermined parameters used to narrow the pleural line search, e.g., an estimated depth range. The same or similar techniques used to identify candidate pleural lines may be implemented to identify A-lines. Block 312 may encompass processes that may be implemented by a data processor, for example data processor 120.

At block 314, the method 300 involves “computing an A-line intensity of at least one of the A-lines.” Techniques implemented at block 314 may involve the same or similar techniques applied at step 312 for detecting one or more candidate pleural lines and A-lines. Block 314 may be implemented by a signal processor (e.g., signal processor 116) alone or in conjunction with a data processor (e.g., data processor 120). In some examples, the data processor may filter out intensity values received from the signal processor that do not align with previously identified A-line coordinates.

The method 300 at block 316 involves “applying the computed A-line intensity to indicate a target placement of the ultrasound probe for pleural line identification during image data acquisition of the region.” Block 316 may be performed in real time, or in substantially real time, as each ultrasound data frame is received by a data processor, for example. In some embodiments, block 316 may be implemented by A-line intensity thresholding and/or by comparing A-line intensity values in successively received data frames.

It will be understood that each block of the flowchart, and combinations of blocks in the flowchart, may be implemented by various means, such as hardware, firmware, processor(s), circuitry and/or other devices associated with the execution of software including one or more computer program instructions. For example, one or more of the procedures described may be embodied by computer program instructions. In this regard, the computer program instructions which embody the procedures described above may be stored by a memory and executed by a processor. As will be appreciated, any such computer program instructions may be loaded onto a computer or other programmable apparatus (e.g., hardware) to produce a machine, such that the instructions which execute on the computer or other programmable apparatus create means for implementing the functions specified in the flowchart block(s). These computer program instructions may also be stored in a computer-readable memory that may direct a computer or other programmable apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture which implements the functions specified in the flowchart block(s).

Referring to FIG. 4, an ultrasound imaging system 400 constructed in accordance with the principles of the present invention is shown in block diagram form. The ultrasound imaging system 400 includes additional components, not shown in FIG. 1, which may be included within a system configured to identify the target placement of the ultrasound probe. For example, any of the above-described functions of the data processor 120 may be programmed (e.g., via computer executable instructions) into an existing processor of the system 400. In some embodiments, the functions of the data processor 120 may be implemented in and/or controlled by one or more of the processing components shown in FIG. 4, including for example, the B mode processor 428, scan converter 430, multiplanar reformatter 432, volume renderer 434, and/or image processor 436.

In the ultrasonic imaging system of FIG. 4, an ultrasound probe 412 includes a transducer array 414 for transmitting ultrasonic waves and receiving echo information regarding a pleural line and one or more corresponding A-lines. The transducer array 414 is coupled to a microbeamformer 416 in the probe 412 which controls transmission and reception of signals by the transducer elements in the array. In this example, the microbeamformer 416 is coupled by the probe cable to a transmit/receive (T/R) switch 418, which switches between transmission and reception and protects the main beamformer 422 from high energy transmit signals. In some embodiments, the T/R switch 418 and other elements in the system can be included in the transducer probe rather than in a separate ultrasound system base. The transmission of ultrasonic beams from the transducer array 414 under control of the microbeamformer 416 is directed by the transmit controller 420 coupled to the T/R switch 418 and the beamformer 422, which receives input from the user's operation of the user interface or control panel 424. One of the functions controlled by the transmit controller 420 is the direction in which beams are steered. Beams may be steered straight ahead from (orthogonal to) the transducer array, or at different angles for a wider field of view. The partially beamformed signals produced by the microbeamformer 416 are coupled to a main beamformer 422 where partially beamformed signals from individual patches of transducer elements are combined into a fully beamformed signal.

The beamformed signals are coupled to a signal processor 426. Like signal processor 118, signal processor 426 can process the received echo signals in various ways, such as bandpass filtering, decimation, I and Q component separation, and harmonic signal separation. The signal processor 426 may also perform additional signal enhancement such as speckle reduction, signal compounding, and noise elimination. The processed signals are coupled to a B mode processor 428, which can employ amplitude detection for the imaging of structures in the body, including the pleural interface. The signals produced by the B mode processor are coupled to a scan converter 430 and a multiplanar reformatter 432. The scan converter 430 arranges the echo signals in the spatial relationship from which they were received in a desired image format. For instance, the scan converter 430 may arrange the echo signal into a two dimensional (2D) sector-shaped format, or a pyramidal three dimensional (3D) image. The multiplanar reformatter 432 can convert echoes which are received from points in a common plane in a volumetric region of the body into an ultrasonic image of that plane, as described in U.S. Pat. No. 6,443,896 (Detmer). A volume renderer 434 converts the echo signals of a 3D data set into a projected 3D image as viewed from a given reference point, e.g., as described in U.S. Pat. No. 6,530,885 (Entrekin et al.) The 2D or 3D images are coupled from the scan converter 430, multiplanar reformatter 432, and volume renderer 434 to an image processor 436 for further enhancement, buffering and temporary storage for display on an image display 438. The graphics processor 436 can generate graphic overlays for display with the ultrasound images. These graphic overlays can contain, e.g., standard identifying information such as patient name, date and time of the image, imaging parameters, and the like. Graphic overlays may also include one or more signals indicating the target placement of the probe has been obtained and/or that the current probe position and/or orientation is closer or further from the target placement, based on measured variations in A-line intensity. For these purposes the graphics processor receives input from the user interface 424, such as a typed patient name. The user interface 424 may also receive input prompting adjustments in the settings and/or parameters used by the system 400. The user interface can also be coupled to the multiplanar reformatter 432 for selection and control of a display of multiple multiplanar reformatted (MPR) images.

FIG. 5 shows a lung ultrasound image 500 obtained from a sub-optimal position and/or orientation of an ultrasound probe. FIG. 5 shows a lung 510 and a pleural line 512 displayed in a B-mode image. As shown, the pleural line 512 is unclear, with the interface between lung tissue and air appearing ill-defined and fuzzy. Due to this lack of image clarity, automatic detection of the pleural line may be difficult, which may interfere with or even rendering inoperable one or more assistance features that may be reliant on automatic pleural line detection. An unclear pleural line, such as that shown in FIG. 5, may also complicate examination of the pleural line. A clinician examining FIG. 5, for example, may be unable to identify certain lung characteristics such as the thickness of the pleural interface and/or the occurrence of lung sliding.

FIG. 6 shows a lung ultrasound image 600 obtained via an ultrasound probe positioned and/or oriented in the target placement according to the embodiments described herein. FIG. 6 depicts a lung 610 that includes a pleural line 612 and an A-line 614. FIG. 6 also depicts an example of a probe position/orientation indicator 616. Relative to FIG. 5, the pleural line 612 is noticeably more bright, clear, and otherwise visible. The A-line 614 appears at approximately twice the depth of the pleural line 612. The probe position/orientation indicator 616 displayed in FIG. 6 may indicate to a user that the pleural line 612 shown in the image 600 represents the pleural line image produced by a target placement of the probe. In the embodiment shown, the probe position/orientation indicator 616 is a green, triangular graphic. In other embodiments, the indicator 616 may be any other shape, color, and/or size. The position of the indicator 616 on the user interface may also vary. As shown, the indicator 616 is positioned in an upper left corner, however, in other examples, the indicator 616 may be positioned elsewhere. In some embodiments, the indicator 616 might not include a displayed graphic at all, instead including an audio cue and/or tactile stimulation, for example. Using the image 600 shown in FIG. 6, a clinician may be able to identify various characteristics of the pleural line and/or additional features. Automated identification processes that rely on pleural line detection may also be performed with greater ease and accuracy using the image 600.

Of course, it is to be appreciated that any one of the examples, embodiments or processes described herein may be combined with one or more other examples, embodiments and/or processes or be separated and/or performed amongst separate devices or device portions in accordance with the present systems, devices and methods. The above-discussion is intended to be merely illustrative of the present system and should not be construed as limiting the appended claims to any particular embodiment or group of embodiments. Thus, while the present system has been described in particular detail with reference to exemplary embodiments, it should also be appreciated that numerous modifications and alternative embodiments may be devised by those having ordinary skill in the art without departing from the broader and intended spirit and scope of the present system as set forth in the claims that follow. Accordingly, the specification and drawings are to be regarded in an illustrative manner and are not intended to limit the scope of the appended claims. 

1. An ultrasound imaging system comprising: an ultrasound probe configured to receive ultrasound echoes from a subject to image a region of the subject; a data processor in communication with the ultrasound probe, the data processor configured to: identify one or more candidate pleural lines and one or more A-lines corresponding to the candidate pleural lines; compute an A-line intensity of at least one of the A-lines; and apply the computed A-line intensity to indicate a target placement of the ultrasound probe for imaging the region for pleural line identification.
 2. The ultrasound imaging system of claim 1, further comprising a user interface in communication with the data processor, the user interface configured to alert the user of the target placement of the ultrasound probe.
 3. The ultrasound imaging system of claim 1, wherein the computed A-line intensity exceeds a predetermined threshold when the target placement is satisfied.
 4. The ultrasound imaging system of claim 1, wherein the target placement involves a position or an orientation of the ultrasound probe.
 5. The ultrasound imaging system of claim 1, wherein the data processor is further configured to reject one or more candidate pleural lines by determining whether one or more candidate pleural lines satisfy a predetermined pleural line intensity threshold.
 6. The ultrasound imaging system of claim 1, wherein the data processor is further configured to identify one or more sub-regions of an ultrasound data frame that correspond to an estimated depth of one or more candidate pleural lines.
 7. The ultrasound imaging system of claim 1, wherein the data processor is further configured to identify one or more sub-regions of an ultrasound data frame that correspond to an estimated depth of one or more A-lines.
 8. The ultrasound imaging system of claim 1, wherein the data processor is further configured to identify a first A-line intensity measured at a first time, and a second A-line intensity measured at a second time, the first time different from the second time.
 9. The ultrasound imaging system of claim 8, wherein the data processor is further configured to identify an A-line intensity variation, the A-line intensity variation equal to an intensity difference between the first A-line intensity and the second A-line intensity.
 10. The ultrasound imaging system of claim 2, wherein the user interface is configured to alert the user by providing an indicator to the user, wherein the indicator is configured to provide an absolute signal, such that the signal is either in an “On” state when the probe is in the target placement or an “Off” state when the probe is not in the target placement.
 11. The ultrasound imaging system of claim 2, wherein the user interface is configured to alert the user by providing an indicator to the user, wherein the indicator is configured to provide a relative signal that changes in response to variations in A-line intensity that result from repositioning or reorienting the ultrasound probe.
 12. The ultrasound imaging system of claim 1, wherein the one or more A-lines appear at depths that are about multiple integers of a depth of the one or more candidate pleural lines.
 13. A method comprising: acquiring image data of a region of a lung tissue via an ultrasound probe; detecting, using the data, one or more candidate pleural lines and one or more A-lines corresponding to the candidate pleural lines; computing an A-line intensity of at least one of the A-lines; applying the computed A-line intensity to indicate a target placement of the ultrasound probe for pleural line identification during image data acquisition of the region.
 14. The method of claim 13, further comprising alerting a user of the target placement of the ultrasound probe via a user interface.
 15. The method of claim 13, wherein the computed A-line intensity exceeds a predetermined threshold when the target placement is satisfied.
 16. The method of claim 13, wherein the target placement involves a position or an orientation of the ultrasound probe.
 17. The method of claim 13, wherein detecting, using the data, one or more candidate pleural lines comprises determining whether one or more unidentified lines are located within a predetermined depth range.
 18. The method of claim 13, wherein detecting, using the data, one or more candidate pleural lines comprises determining whether one or more unidentified lines satisfy a predetermined pleural line intensity threshold.
 19. The method of claim 13, wherein detecting, using the data, one or more A-lines comprises applying a Hough transform to the data.
 20. The method of claim 13, wherein detecting, using the data, one or more A-lines comprises determining a depth corresponding to a peak intensity level detected at one or more lateral positions in the region of the lung tissue.
 21. A non-transitory computer-readable medium comprising executable instructions, which when executed cause one or more processors of medical imaging system to perform the method of claim
 13. 